Solvent-accessible surface, simulations

If this hypothesis is true, one could expect the solvent-accessible surface area (ASA) of the polypeptide backbone in the PPII conformation to be correlated with measured PPII helix-forming propensities. In order to test this, Monte Carlo computer simulations of short peptides Ac-Ala-Xaa-Ala-NMe (Xaa = Ala, Asn, Gin, Gly, lie, Leu, Met, Pro, Ser, Thr, and Val) were run. These particular residues were examined because their... 

PPII helix-forming propensities have been measured by Kelly et al. (2001) and A. L. Rucker, M. N. Campbell, and T. P. Creamer (unpublished results). In the simulations the peptide backbone was constrained to be in the PPII conformation, defined as (0,VO = ( — 75 25°, +145 25°), using constraint potentials described previously (Yun and Hermans, 1991 Creamer and Rose, 1994). The AMBER/ OPLS potential (Jorgensen and Tirado-Rives, 1988 Jorgensen and Severance, 1990) was employed at a temperature of 298° K, with solvent treated as a dielectric continuum of s = 78. After an initial equilibration period of 1 x 104 cycles, simulations were run for 2 x 106 cycles. Each cycle consisted of a number of attempted rotations about dihedrals equal to the total number of rotatable bonds in the peptide. Conformations were saved for analysis every 100 cycles. Solvent-accessible surface areas were calculated using the method of Richmond (1984) and a probe of 1.40 A radius. 

The sum of the estimated average solvent-accessible surface areas, (ASA), for the peptide units (—CO—NH—) on either side of residue Xaa, plus the Ca of Xaa, in each peptide simulated are given in Table II. Also shown are the estimated PPII helix-forming propensities for each residue measured by Kelly et al. (2001) and A. L. Rucker, M. N. Campbell, and... 

Kaznessis et al. [24] used Monte Carlo simulations on a data set of 85 molecules collected from various sources, to calculate physically significant descriptors such as solvent accessible surface area (SASA), solute dipole, number of hydrogen-bond acceptors (HBAC) and donors (HBDN), molecular volume (MVOL), and the hydrophilic, hydrophobic, and amphiphilic components of SASA and related them with BBB permeability using the MLR method. After removing nine strong outliers, the following relationship was developed (Eq. 37) ... 

Carrying out the same simulation that produces solvent-accessible surface displays, but locating the dots at the center of the probe molecule, produces the extended surface of the model. This display is useful for studying inter-molecular contacts. If the user brings two models together—one with extended surface displayed, the other as a simple stick model—the points of intermo-lecular contact are where the extended surface of one model touches the atom centers of the second model. 

The most expensive part of a simulation of a system with explicit solvent is the computation of the long-range interactions because this scales as Consequently, a model that represents the solvent properties implicitly will considerably reduce the number of degrees of freedom of the system and thus also the computational cost. A variety of implicit water models has been developed for molecular simulations [56-60]. Explicit solvent can be replaced by a dipole-lattice model representation [60] or a continuum Poisson-Boltzmann approach [61], or less accurately, by a generalised Bom (GB) method [62] or semi-empirical model based on solvent accessible surface area [59]. Thermodynamic properties can often be well represented by such models, but dynamic properties suffer from the implicit representation. The molecular nature of the first hydration shell is important for some systems, and consequently, mixed models have been proposed, in which the solute is immersed in an explicit solvent sphere or shell surrounded by an implicit solvent continuum. A boundary potential is added that takes into account the influence of the van der Waals and the electrostatic interactions [63-67]. 

In the work of Zachmann et al. new approaches to the quantification of surface flexibility have been suggested. The basis data for these approaches are supplied by molecular dynamics (MD) simulations. The methods have been applied to two proteins (PTI and ubiquitin). The calculation and visualization of the local flexibility of molecular surfaces is based on the notion of the solvent accessible surface (SAS), which was introduced by Connolly. For every point on this surface a probability distribution p(r) is calculated in the direction of the surface normal, i.e., the rigid surface is replaced by a soft surface. These probability distributions are well suited for the interactive treatment of molecular entities because the former can be visualized as color coded on the molecular surface although they cannot be directly used for quantitative shape comparisons. In Section IV we show that the p values can form the basis for a fuzzy definition of vaguely defined surfaces and their quantitative comparison. 

Solvation nmdels. 934 Solvent-accessible surfaces. 922 Solvents, in molecular dynamics simulations. 9.34... 

GB/S A Generalized-Born/Surface-Area. A method for simulating solvation implicitly, developed by W.C. Still s group at Columbia University. The solute-solvent electrostatic polarization is computed using the Generalized-Born equation. Nonpolar solvation effects such as solvent-solvent cavity formation and solute-solvent van der Waals interactions are computed using atomic solvation parameters, which are based on the solvent accessible surface area. Both water and chloroform solvation can be emulated. 

Fig. 4.8. Ion-oxygen distance for a 100-ps interval simulation for Sm (bottom). The plot illustrates the equilibrium between eight- and nine-fold coordination. The volume Vjas that is enclosed by the solvent-accessible surface of the [Sm(H20)g/9] aqua ion is shown as a function of time (top).

Figure 5-5 Comparison of structures of the TT region of (a) duplex 1, and (b) native duplex in B-form DNA. Both strands were cut out of the full duplexes, generated (a) from molecular dynamics simulations incorporating NMR constraints, and (b) from crystal structure data [123], The intruding C7 methylene with the flat solvent-accessible surface in the modified linkage 1 contrasts markedly with the maximally solvent-accessible phosphate of the phosphodiester linkage. The solvent-accessible surfaces are stippled (adapted from [72]).

Fig. 1 Molecular simulation of a microporous hypercrossUnked polydichloroxylene network (a-c) and simulation of hydrogen sorption within the micropores (d) [31]. This model simulates properties such as pore volume, density, and average pore size quite well. Hydrogen sorption is overestimated by the simulation shown in (d) because a Connolly surface, rather than a solvent accessible surface [30], is used to calculate the uptake...

Fig. 9 Atomistic simulations for PAE networks with different strut lengths [19]. Node-strut topology for simulated network fragments for CMP-0 (left), CMP-1 centre), and CMP-5 right), (a). Atomistic simulations of network fragments for CMP-0, CMP-1, CMP-2, CMP-3, and CMP-5 left to right), (b). A solvent accessible surface is shown (in green) in each case (solvent diameter =0.182 nm)...

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